In this work, we measured the time evolution of the transmission features of 10–100 keV protons transmitted through nanocapillaries in a polycarbonate (PC) membrane. After reaching equilibrium, transmitted particles with an incident energy of 100 keV were located around the direction along the incident beam but not along the capillary axis, indicating that the transport mechanism of the 100 keV ion was distinct from that of keV-energy ions. The simulation results indicated that charge-patch-assisted collective scatterings on the surface are the main transport mechanism for the hundred-keV ions in nanocapillaries. This scenario fills in the gap in the previous understanding of ion transmission in nanocapillaries from keV to MeV energies.

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The optical properties and performance of the two-dimensional photonic crystal (2D PhC) filters at normal incidence were simulated, and the best geometric parameters were obtained with the help of a global optimization program. The honeycomb structure has better performance, including high in-band transmittance, high out-band reflectance, and low parasitic absorption. The power density performance and conversion efficiency can reach 80.6% and 62.5%. Furthermore, the deeper cavity structure and multi-layer structure were designed to improve the performance of the filter. The deeper one can reduce the influence of transmission diffraction, increases the power density performance and conversion efficiency. The multi-layer structure reduces the parasitic absorption significantly and increases the conversion efficiency to 65.5%. These filters have both high efficiency and high power density, avoid the challenge of high-temperature stability faced by emitters, also easier and cheaper to fabricate compared to the 2D PhC emitters. These results suggest that the 2D PhC filters can be used in thermophotovoltaic systems for long-duration missions to improve the conversion efficiency.

Background: Hepatocellular carcinoma is one kind of clinical common malignant tumor with a poor prognosis, and its pathogenesis remains to be clarified urgently. This study was performed to elucidate key genes involving HCC by bioinformatics analysis and experimental evaluation.Methods: We identified common differentially expressed genes (DEGs) based on gene expression profile data of GSE60502 and GSE84402 from the Gene Expression Omnibus (GEO) database. Gene Ontology enrichment analysis (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, REACTOME pathway enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were used to analyze functions of these genes. The protein-protein interaction (PPI) network was constructed using Cytoscape software based on the STRING database, and Molecular Complex Detection (MCODE) was used to pick out two significant modules. Hub genes, screened by the CytoHubba plug-in, were validated by Gene Expression Profiling Interactive Analysis (GEPIA) and the Human Protein Atlas (HPA) database. Then, the correlation between hub genes expression and immune cell infiltration was evaluated by Tumor IMmune Estimation Resource (TIMER) database, and the prognostic values were analyzed by Kaplan-Meier plotter. Finally, biological experiments were performed to illustrate the functions of RRM2.Results: Through integrated bioinformatics analysis, we found that the upregulated DEGs were related to cell cycle and cell division, while the downregulated DEGs were associated with various metabolic processes and complement cascade. RRM2, MAD2L1, MELK, NCAPG, and ASPM, selected as hub genes, were all correlated with poor overall prognosis in HCC. The novel RRM2 inhibitor osalmid had anti-tumor activity, including inhibiting proliferation and migration, promoting cell apoptosis, blocking cell cycle, and inducing DNA damage of HCC cells.Conclusion: The critical pathways and hub genes in HCC progression were screened out, and targeting RRM2 contributed to developing new therapeutic strategies for HCC.